In many applications, an image sensor is coupled to a processing device enabling to extract, from the images acquired by the sensor, data useful for the application.
Conventionally, the processing device is capable of transposing or projecting an image acquired by the sensor in a specific representation domain different from the acquisition domain, to exacerbate certain characteristics of the image selected according to the considered application.
For example, in a face detection application, the image supplied by the sensor may be projected in a representation domain selected to highlight a specific pattern, easily detectable, when a face is present in the image.
The image projection operation generally goes along with a decrease in dimensions, that is, the dimension (number of values) of the image projection is generally smaller than the dimension of the original image. This enables to decrease the complexity and the memory and energy resource needs of possible subsequent processings.
The projection of an image supplied by the sensor in a representation domain different from the acquisition domain is conventionally performed by multiplying the original image by a transition matrix. Such an operation however requires relatively significant memory and calculation resources. This may raise an issue in certain applications, for example, so-called real-time applications, where images are desired to be processed on the fly, along their acquisition by the sensor.
It would be desirable to have an acquisition system comprising a sensor capable of successively supplying a plurality of measured values, and a device of on-the-fly processing of the values supplied by the sensor, the processing device enabling to perform a projection of a set of values supplied by the sensor is a representation domain different from the acquisition domain, the system overcoming all or part of the disadvantages of known systems.